Methods and systems for generating communications associated with optimization codes

ABSTRACT

This disclosure is directed to systems and methods for generating a communication associated with an optimization code. Generating a communication may include generating an optimization code, which may include (i) receiving a first data associated with one or more of a first computing device and a first computing device user; (ii) generating at least two confirmation codes, including one or more of a verification code, a consistency code, and an activity code, which may be associated with a comparative accuracy of the first data, a comparative consistency of the first data, and a comparative activity of the first data, respectively; and (iii) generating an optimization code which may be based, at least in part, on the at least two confirmation code and associated with a relative predictability of the first data.

TECHNICAL FIELD

The present disclosure relates in general to the field of communicationsand more particularly to the generation of optimization codes and theiruse in generating communications.

BACKGROUND

Target communicators need faster and more efficient tools to evaluatethird-party data and optimize performance of communications.

SUMMARY

According to some embodiments, a method for generating, at one or moreservers, a communication associated with an optimization code maycomprise: receiving, at the one or more servers and from a firstcomputing device, a first data associated with the first computingdevice and a first computing device user, the first data comprising atleast one trait associated with the first computing device user andwherein the at least one trait is associated with a second data;generating at the one or more servers, at least two confirmation codes,wherein each of the at least two confirmation codes comprises at leastone of: a verification code, wherein the verification code is based on athird data and a comparison of at least one verified trait associatedwith the first computing device user to the second data associated withthe at least one trait associated with the first computing device user;and associated with a comparative accuracy of the second data associatedwith the at least one trait; a consistency code, wherein the consistencycode is: based on a comparison of a fourth data to the first data; andassociated with a comparative consistency of the first data; and anactivity code, wherein the activity code is: based on an aggregation ofa fifth data; and associated with a comparative activity of the firstdata; storing the at least two confirmation codes at a databaseassociated with the one or more servers; retrieving, at the one or moreservers and from the database associated with the one or more servers,at least one retrieved confirmation code; generating, at the one or moreservers, at least one raw index, wherein the at least one raw index isbased on the at least one retrieved confirmation code and wherein the atleast one raw index is generated by transforming the at least oneretrieved confirmation code; generating, at the one or more servers, atleast one comparative index, wherein the at least one comparative indexis based on the at least one raw index and is generated by transformingthe at least one raw index; generating, at the one or more servers, arelative locus associated with the at least one comparative index;generating, at the one or more servers, the optimization code, whereinthe optimization code is based on the relative locus and is associatedwith a relative predictability of the first data; and generating, at theone or more servers, the communication based on the optimization code.

According to some embodiments, one of the at least two confirmationcodes comprises the verification code, wherein the verification code isgenerated at the one or more servers by: receiving the third data from asecond computing device, wherein the third data comprises the at leastone verified trait associated with the first computing device user;generating the comparison by comparing the at least one verified traitassociated with the first computing device user to the second dataassociated with the at least one trait associated with the firstcomputing device user; and generating the verification code.

According to some embodiments, one of the at least two confirmationcodes comprises the consistency code, wherein the consistency code isgenerated at the one or more servers by: receiving the fourth data;comparing the fourth data to the first data; and generating theconsistency code.

According to some embodiments, one of the at least two confirmationcodes comprises the activity code, wherein the activity code isgenerated at the one or more servers by: receiving the fifth data;aggregating the fifth data; and generating the activity code.

According to some embodiments, the fourth data is associated with one ormore of: contamination of the second data associated with the at leastone trait associated with the first computing device user; randomuser-generated data, wherein the random user-generated data comprisessecond data not associated with the at least one trait associated withthe first computing device user; and theoretical model data, wherein thetheoretical model data comprises predictions based on historical dataand uses information associated with the first data to further refine atheoretical model.

According to some embodiments, the fifth data is associated with one ormore of: the comparative activity of computing device users associatedwith the at least one trait associated with the first computing deviceuser; percentage of unique computing device users associated with the atleast one trait associated with the first computing device user during agiven period; and recentness of information associated with the at leastone trait associated with the first computing device user.

According to some embodiments, a method comprises generating threeconfirmation codes comprising one each of the verification code, theconsistency code, and the activity code.

According to some embodiments, the second data comprises textualdescriptions.

According to some embodiments, the second data comprises categories.

A method for generating a communication associated with an optimizationcode may comprise: receiving, at the one or more servers and from afirst computing device, a first data associated with the first computingdevice and a first computing device user, the first data comprising atleast one trait associated with the first computing device user andwherein the at least one trait is associated with one or more seconddata; generating at the one or more servers, at least three confirmationcodes, wherein the at least three confirmation codes comprise each of: averification code, wherein the verification code is generated at the oneor more servers by: receiving a third data from a second computingdevice, wherein the third data comprises at least one verified traitassociated with the first computing device user, comparing the at leastone verified trait associated with the first computing device user withthe second data associated with the at least one trait associated withthe first computing device user, and generating the verification code,wherein the verification code is based on a comparison of the at leastone verified trait associated with the first computing device user withthe second data associated with the at least one trait associated withthe first computing device user and is associated with a comparativeaccuracy of the second data associated with the at least one trait; aconsistency code, wherein the consistency code is generated at the oneor more servers by: receiving a fourth data, wherein the fourth data isassociated with any one or more of: contamination of the second dataassociated with the at least one trait associated with the firstcomputing device user, random user-generated data, wherein the randomuser-generated data comprises second data not associated with the atleast one trait associated with the first computing device user, andtheoretical model data, wherein the theoretical model data comprisespredictions based on historical data and uses information associatedwith the first data to further refine a theoretical model, comparing thefourth data to the first data, and generating the consistency code,wherein the consistency code is based on the comparison of the fourthdata to the first data and is associated with a comparative consistencyof the first data; an activity code, wherein the activity code isgenerated at the one or more servers by: receiving a fifth data, whereinthe fifth data is associated with any one or more of: comparativeactivity of computing device users associated with the at least onetrait associated with the first computing device user, percentage ofunique computing device users associated with the at least one traitassociated with the first computing device user during a given period,and recentness of information associated with the at least one traitassociated with the first computing device user, aggregating the fifthdata, and generating the activity code, wherein the activity code isbased on the aggregation of the fifth data and is associated with acomparative activity of the first data; storing the two or moreconfirmation codes at a database associated with the one or moreservers; retrieving, at the one or more servers and from the databaseassociated with the one or more servers, at least one retrievedconfirmation code; generating, at the one or more servers, at least oneraw index, wherein the at least one raw index is based on the at leastone retrieved confirmation code and wherein the at least one raw indexis generated by transforming the at least one retrieved confirmationcode; generating, at the one or more servers, at least one comparativeindex, wherein the comparative index is based on the at least one rawindex and is generated by transforming the at least one raw index;generating, at the one or more servers a relative locus associated withthe at least one comparative index; generating, at the one or moreservers, the optimization code, wherein the optimization code is basedon the relative locus and is associated with a relative predictabilityof the first data; and generating, at the one or more servers, thecommunication based on the optimization code.

In some embodiments, a method may comprise generating three confirmationcodes comprising one each of the verification code, the consistencycode, and the activity code.

A system may comprise a server, the server comprising: a memorycomprising server instructions; and a processing device configured forexecuting the server instructions, wherein the server instructions causethe processing device to perform operations of: receiving, at one ormore of the servers and from a first computing device, a first dataassociated with the first computing device and a first computing deviceuser, the first data comprising at least one trait associated with thefirst computing device user and wherein the at least one trait isassociated with one or more second data; generating at one or more ofthe servers, at least two confirmation codes, wherein each of the atleast two confirmation codes comprises at least one of: a verificationcode, wherein the verification code is: based on a comparison of atleast one verified trait associated with the first computing device userto the second data associated with the at least one trait associatedwith the first computing device user; and associated with a comparativeaccuracy of the second data associated with the at least one trait; aconsistency code, wherein the consistency code is: based on a comparisonof a fourth data to the first data; and associated with a comparativeconsistency of the first data; and an activity code, wherein theactivity code is: based on an aggregation of a fifth data; andassociated with a comparative activity of the first data; storing thetwo or more confirmation codes at a database associated with one or moreof the servers; retrieving, at one or more of the servers and from thedatabase associated with one or more of the servers, at least oneretrieved confirmation code; generating, at one or more of the servers,at least one raw index, wherein the at least one raw index is based onthe at least one retrieved confirmation code and wherein the at leastone raw index is generated by transforming the at least one retrievedconfirmation code; generating, at one or more of the servers, at leastone comparative index, wherein the comparative index is based on the atleast one raw index and is generated by transforming the at least oneraw index; generating, at one or more of the servers a relative locusassociated with the at least one comparative index; generating, at oneor more of the servers, the optimization code, wherein the optimizationcode is based on the relative locus and is associated with a relativepredictability of the first data; and generating, at one or more of theservers, the communication based on the optimization code.

According to some embodiments, one of the at least two confirmationcodes comprises the verification code, and the server instructions causethe processing device to generate the verification code by performingthe operations of: receiving a third data from a second computingdevice, wherein the third data comprises the at least one verified traitassociated with the first computing device user; generating thecomparison by comparing the at least one verified trait associated withthe first computing device user to the second data associated with theat least one trait associated with the first computing device user; andgenerating the verification code.

According to some embodiments, one of the at least two confirmationcodes comprises the consistency code, and the server instructions causethe processing device to generate the consistency code by performing theoperations of: receiving the fourth data; comparing the fourth data tothe first data; and generating the consistency code.

According to some embodiments, one of the at least two confirmationcodes comprises the activity code, and the server instructions cause theprocessing device to generate the activity code by performing theoperations of: receiving the fifth data; aggregating the fifth data; andgenerating the activity code.

According to some embodiments, the fourth data is associated with one ormore of: contamination of the second data associated with the at leastone trait associated with the first computing device user; randomuser-generated data, wherein the random user-generated data comprisessecond data not associated with the at least one trait associated withthe first computing device user; and theoretical model data, wherein thetheoretical model data comprises predictions based on historical dataand uses information associated with the first data to further refine atheoretical model.

According to some embodiments, the fifth data is associated with one ormore of: comparative activity of computing device users associated withthe at least one trait associated with the first computing device user;percentage of unique computing device users associated with the at leastone trait associated with the first computing device user during a givenperiod; and recentness of information associated with the at least onetrait associated with the first computing device user.

According to some embodiments, the server instructions cause theprocessing device to generate three confirmation codes comprising oneeach of the verification code, the consistency code, and the activitycode.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure is illustrated by way of example, and not by way oflimitation in the figures of the accompanying drawings in which likereference numerals are used to refer to similar elements. The variouselements shown in the figures that follow may be optional depending on agiven embodiment without departing from the principles provided in thisdisclosure.

FIG. 1 illustrates a schematic block of a system for generatingcommunications associated with optimization codes, according to someembodiments of the disclosure.

FIG. 2 illustrates a functional block diagram of a method for generatingcommunications associated with optimization codes, according to someembodiments of the disclosure.

FIG. 3 illustrates a system and method for generating communicationsassociated with optimization codes, according to some embodiments of thedisclosure.

FIG. 4 illustrates a system and method for generating communicationsassociated with optimization codes, according to some embodiments of thedisclosure.

FIG. 5 illustrates a system for generating communications associatedwith optimization codes, according to some embodiments of thedisclosure.

DETAILED DESCRIPTION

The present disclosure relates to systems and methods for generatingcommunications associated with optimization codes. Generation ofoptimization codes may be associated with assessing and ranking thequality of third-party data segments based on an objective assessment ofcriteria designed to reflect the accuracy, optimization potential, andpredictability of third-party data segments.

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant teachings. However, the present teachings may be practicedwith or without such specific details. In other instances, well-knownmethods, procedures, components, and/or circuitry have been described ata relatively high level, without detail, in order to avoid unnecessarilyobscuring aspects of the present teachings. The various technologiesdescribed in this specification generally relate to communications incomplex computing networks, which may be used to monitor, used toinitiate, or may be otherwise associated with execution events.

It is understood that any features of any embodiment described hereinmay be incorporated into any other embodiment described herein. Featuresof different embodiments can be combined to form new embodiments.Further, any one or more of the steps, operations, etc., describedherein may be performed in the order described or in any order. Any oneor more of the steps, operations, etc., described herein may be removedand additional steps may be added. Although the present disclosure isrelated to communications in complex computing networks, it should alsobe understood that any one or more of the methods, systems, operations,etc., described herein may be associated with other types ofcommunications and networks. The terms communication channel and networkcommunication channel may be used interchangeably. It is understood thatany reference to a communication channel (e.g., first communicationchannel, second communication channel, third communication channel) orto a network communication channel (e.g., first network communicationchannel, second network communication channel, etc.) could mean anycommunication channel. For example, a first communication channel and asecond communication channel could be the same communication channel ordifferent communication channels.

The figures and descriptions provided herein may have been simplified toillustrate aspects that are relevant for a clear understanding of theherein described devices, systems, and methods, while eliminating, forthe purpose of clarity, other aspects that may be found in typicalsimilar devices, systems, and methods. Those of ordinary skill in theart may recognize that other elements and/or operations may be desirableand/or necessary to implement the devices, systems, and methodsdescribed herein. But because such elements and operations are wellknown in the art, and because they do not facilitate a betterunderstanding of the present disclosure, a discussion of such elementsand operations may not be provided herein. However, the presentdisclosure is deemed to inherently include all such elements,variations, and modifications to the described aspects that would beknown to those of ordinary skill in the art.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. Forexample, as used herein, the singular forms “a”, “an” and “the” may beintended to include the plural forms as well, unless the context clearlyindicates otherwise. The terms “comprises,” “comprising,” “including,”and “having,” are inclusive and therefore specify the presence of statedfeatures, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof. The method steps, processes, and operations described hereinare not to be construed as necessarily requiring their performance inthe particular order discussed or illustrated, unless specificallyidentified as an order of performance. It is also to be understood thatadditional or alternative steps may be employed.

Although the terms first, second, third, etc., may be used herein todescribe various elements, components, regions, layers and/or sections,these elements, components, regions, layers and/or sections should notbe limited by these terms. These terms may be only used to distinguishone element, component, region, layer or section from another element,component, region, layer or section. That is, terms such as “first,”“second,” and other numerical terms, when used herein, do not imply asequence or order unless clearly indicated by the context.

A system for generating a communication associated with an optimizationcode may comprise one or more servers, which may comprise (i) a memorycomprising server instructions and (ii) a processing device configuredfor executing the server instructions. According to some embodiments,the server instructions may cause the processing device to perform oneor more of the operations described below.

Illustrated in FIG. 1 is a high level system 1000 for generating acommunication associated with an optimization code. An optimization codemay be associated with assessing and ranking the quality of third-partydata segments according to some embodiments of this disclosure. In thedepicted implementation, the system 1000 may comprise a server 1020,which may perform the operation of receiving, at one or more servers1020 or on an external server and from a first computing device 1010, afirst data 1014 associated with the first computing device 1010 and afirst computing device user 1012. The first data 1014 may comprise atleast one trait associated with the first computing device user 1012,wherein the at least one trait is associated with one or more seconddata 1022. According to some embodiments, a first data 1014 may becomprised of a string of alphanumeric and/or symbolic characters of anylength and may be associated with one or a combination of traitsassociated with a first computing device user 1012. For example, in someembodiments, a trait may be any one or more of height, weight,geolocation, age, gender, sex, marital status, etc. In some embodiments,the trait may be any trait that may describe a user of the system or ofa computing device (e.g., first, second, third computing devices). Afirst data 1014 may be associated with a first computing device. Forexample, where a first device user may be a user of multiple devices, afirst data 1014 may identify the particular computing device associatedwith the first user at a particular time.

Each trait may be associated with a second data 1022. A second data 1022may be comprised of a string of alphanumeric and/or symbolic charactersof any length and may be associated with a description of a trait. Forexample, where a trait is height, a second data 1022 may indicate aheight of “5 feet, 10 inches.” In another example, where a trait is sex,a second data 1022 may indicate a sex of “Female.”

A server 1020 may perform the operation of using the received data(e.g., first data 1014, second data 1022) to generate at least twoconfirmation codes 1030. A confirmation code 1030 may be generated bytransforming the received data (e.g., first data 1014, second data1022), which may include, but is not limited to, e.g. combining,separating, separating and recombining, reordering, comparing, hashing,encrypting, stacking, organizing, and performing mathematical operationson the received data (e.g., first data 1014, second data 1022). Morerobust descriptions of generating potential confirmation codes 1030,according to some embodiments, are disclosed below in conjunction withthe methods.

A confirmation code 1030 may include any one or more of a verificationcode (hereinafter, a “V-code 1024”), a consistency code 1026(hereinafter, a “C-code 1026”), and an activity code 1028 (hereinafter,an “A-code 1028”). Although these confirmation code 1030 embodiments,and the methods of generating them, are described in detail throughoutthe specification, a reader should appreciate that a confirmation code1030 is not limited to these embodiments, and that a confirmation code1030, according to this disclosure, may comprise any code (e.g., anystring of alphanumeric and/or symbolic characters of any length) that isgenerated by transforming (e.g. combining, separating, separating andrecombining, reordering, comparing, hashing, encrypting, stacking,organizing, and performing mathematical operations) a gathered data(e.g., first data 1014, second data 1022, third data, fourth data, fifthdata, etc.).

A server 1020 may perform the operation of causing the two or moreconfirmation codes 1030 to be stored at a database associated with theone or more servers 1020. In some embodiments, at least one (e.g., oneor more) stored confirmation code 1030 may be retrieved at the one ormore servers 1020 and from the database associated with the one or moreservers 1020.

A server 1020 may perform the operation of using the one or moreretrieved confirmation codes 1030 to generate a raw index 1040. The rawindex 1040 may be generated by transforming at least one retrievedconfirmation code 1030, which may include, but is not limited to, e.g.combining, separating, separating and recombining, reordering,comparing, hashing, encrypting, stacking, organizing, and performingmathematical operations on the at least one retrieved confirmation code1030. More robust descriptions of generating a raw index 1040, accordingto some embodiments, are disclosed below in conjunction with themethods.

A server 1020 may perform the operation of using the raw index 1040 togenerate at least one comparative index 1050. The comparative index 1050may be generated by transforming the raw index 1040, which may include,but is not limited to, e.g. combining, separating, separating andrecombining, reordering, comparing, hashing, encrypting, stacking,organizing, and performing mathematical operations on the raw index1040. More robust descriptions of generating at least one comparativeindex 1050, according to some embodiments, are disclosed below inconjunction with the methods.

A server 1020 may perform the operation of using the comparative index1050 to generate a relative locus, which may be associated with thecomparative index 1050. The relative locus may be generated bytransforming the comparative index 1050, which may include, but is notlimited to, e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations on the comparative index 1050. Morerobust descriptions of generating comparative locus, according to someembodiments, are disclosed below in conjunction with the methods.

A server 1020 may perform the operation of using the relative locus togenerate an optimization code 1060. The optimization code 1060 may begenerated by transforming the relative locus, which may include, but isnot limited to, e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations on the relative locus. More robustdescriptions of generating an optimization code 1060, according to someembodiments, are disclosed below in conjunction with the methods.

A server 1020 may perform the operation of using the comparative index1050 to generate an optimization code 1060. The optimization code 1060may be generated by transforming the comparative index 1050, which mayinclude, but is not limited to, e.g. combining, separating, separatingand recombining, reordering, comparing, hashing, encrypting, stacking,organizing, and performing mathematical operations on the comparativeindex 1050. More robust descriptions of generating an optimization code1060, according to some embodiments, are disclosed below in conjunctionwith the methods.

A server 1020 may perform the operation of using the optimization code1060 to generate one or more communications 1065 that can then betransmitted to a third computing device 1080. In some embodiments, anoptimization code 1060 may indicate the desirability of a target of acommunication 1065. For example, in some embodiments, an optimizationcode 1060 may indicate the likelihood that the target of a communicationpossesses certain desired characteristics. In some embodiments, anoptimization code 1060 may indicate whether or not a target meets thethreshold criteria to receive a communication.

One embodiment of the present disclosure is illustrated in FIG. 2 wherea method for generating a communication associated with an optimizationcode may comprise any one or a combination of: receiving a first datathat is associated with one or more of a first device, a first deviceuser, and a second data 2010; generating at least two confirmation codes(2024, 2026, 2028) in response to one or more of the first data and thesecond data; storing the confirmation codes at a database 2030,generating at least one raw index 2040; generating at least onecomparative index 2050; generating a relative locus 2055; generating anoptimization code 2060; and generating a communication 2065.

A method 2000 for generating a communication associated with anoptimization code may comprise receiving data 2010. In some embodiments,data may comprise a first data, which may be associated with a firstcomputing device and, according to some embodiments, a user of the firstcomputing device. A first data may comprise at least one traitassociated with the first computing device or the first computing deviceuser. A trait may comprise any trait that may describe a first computingdevice or a first computing device user. For example, in someembodiments, a trait may be any one or more of height, weight,geolocation, age, gender, sex, marital status, configuration, operatingsystem description, etc. Each trait may be associated with a seconddata, which may be comprised of a string of alphanumeric and/or symboliccharacters of any length and may be associated with a description of atrait. For example, where a trait is height, a second data may indicatea height of “5 foot, 10 inches.” In another example, where a trait issex, a second data may indicate a sex of “Female.” A second data maycomprise, according to some embodiments, categories (e.g. traits) ortextual descriptions (e.g., 5 foot, 10 inches, Female, etc.).

Received data may be used to generate one or more confirmation codesand, according to some embodiments, may include a V-code 2022, a C-code2024, or an A-code 2026. FIG. 3 illustrates, in some embodiments, amethod by which first data 3014 and second data 3022 associated with afirst computing device user 3012 on a first computing device 3010 may beused to generate at least one of a V-code 3024, a C-code 3026, and anA-code 3028 that may be stored as a confirmation code 3030. Aconfirmation code may comprise any code (e.g., any string ofalphanumeric and/or symbolic characters of any length) and may indicatea value or score based on a value, comparison, etc. In some embodiments,A confirmation code may indicate, without limitation, a yes or no (e.g.,affirmative, negative) value, a descriptive (e.g., very close, mediumclose, not close) value, a numerical value based on a scoring system,etc.

A V-code 3024 may comprise any code (e.g., any string of alphanumericand/or symbolic characters of any length) that is generated bytransforming (e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing,performing mathematical operations, etc.) a gathered data (e.g., firstdata, second data). In some embodiments, A V-code 3024 may be generatedat the one or more servers by receiving a third data 3023 from a secondcomputing device 3011. A third data 3023 may comprise at least oneverified trait associated with the first computing device user 3012. Insome embodiments, a third data 3023 may comprise a fourth data 3025,which may include: potential contamination of the second data 3022associated with the at least one trait associated with the firstcomputing device user 3012; potential random user-generated data; and/ortheoretical model data. A verified trait may comprise any traitincluding, but not limited to, any one or more of height, weight,geolocation, age, gender, sex, marital status, configuration, operatingsystem description, etc. In one example, a verified trait could be averified geolocation tag. A verified trait associated with the firstcomputing device user 3012 may then be compared with the second data3022 associated with the at least one trait associated with the firstcomputing device user 3012 to generate a V-code 3024. To continue theexample above, the geolocation description reported by the second data3022 could be verified against a verified geolocation tag received as athird data 3023. The resulting V-code 3024 may be associated with thecomparative accuracy of the second data 3022 associated with the atleast one unverified trait. As used herein, the term comparativeaccuracy may refer to the accuracy (and/or degree of accuracy) of agathered data (e.g., first data, second data) when it is compared to averified or reliable data (e.g., third data).

A C-code 3026 may comprise any code (e.g., any string of alphanumericand/or symbolic characters of any length) that is generated bytransforming (e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations) a gathered data (e.g., first data,second data). In some embodiments, a C-code 3026 may be generated at theone or more servers by receiving a fourth data 3025. In variousembodiments, the fourth data 3025 could include: potential contaminationof the second data 3022 associated with the at least one traitassociated with the first computing device user 3012; potential randomuser-generated data; and/or theoretical model data. Comparing thevarious types of fourth data 3025 to the first data 3014 may be used togenerate a C-code 3026 that may be associated with the comparativeconsistency of the first data 3014. As used herein, the term comparativeconsistency may refer to the consistency (and/or degree of consistency)of a gathered data (e.g., first data, second data) when it is comparedto a verified or reliable data (e.g., fourth data). A fourth data 3025may include a third data 3023, which may include at least one verifiedtrait associated with the first computing device user 3012. A moredetailed description of a third data 3023 may be found above.

A fourth data 3025 may include potential contamination of the seconddata 3022 associated with the at least one trait associated with thefirst computing device user 3012. Potential contamination of the seconddata 3022 may be determined by the presence of two mutually exclusivecategories in a data segment (e.g., second data 3022). For example, ifthe second data 3022 contains both “male” and “female” as descriptivecategories, a fourth data 3025 may comprise an indication (e.g.,indicator, tag) that the second data 3022 may be contaminated data. Inanother example, if the second data 3022 contains both geolocation datafor the USA and geolocation data for Europe, a fourth data 3025 maycomprise an indication (e.g., indicator, tag) that the second data 3022may be contaminated data.

A fourth data 3025 may include potential random user-generated data.Random user-generated data may comprise second data 3022 that is notaccurately associated with the at least one trait associated with thefirst computing device user. This potential random user-generated data(e.g., fourth data 3025) may be used to determine background (e.g.,coincidental) associations between data in a subset.

A fourth data 3025 may include theoretical model data. Theoretical model(e.g., fourth data 3025) data may be based on predictions that usehistorical data to predict how consistent a second data 3022 is tohistoric trends (e.g., a predictive model). In embodiments where afourth data 3025 comprises theoretical model data of the predictive type(e.g., a predictive model), real-time data may also be used to furtherrefine the theoretical model.

An A-code 3028 may comprise any code (e.g., any string of alphanumericand/or symbolic characters of any length) that is generated bytransforming (e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations) a gathered data (e.g., first data,second data). In some embodiments, an A-code 3028 may be generated atthe one or more servers by receiving a fifth data 3027. In variousembodiments, a fifth data 3027 could include the comparative activity ofthe computing device users associated with a subset of first data 3014,the percentage of unique computing device users associated a subset offirst data 3014, and/or the recentness of the information associatedwith a subset of first data 3014.

A fifth data 3027 may comprise comparative activity of the computingdevice users associated with the at least one trait associated with thefirst computing device user. As used herein, the term comparativeactivity may refer to the accuracy (and/or degree of accuracy) ofactivity associated with (or comprised within) a gathered data (e.g.,first data, second data) when it is compared to a verified or reliabledata regarding activity (e.g., fifth data). For example, a fifth data3027 may comprise, according to some embodiments, internet activities,shopping habits, viewing and/or browsing history, information aboutinterests, or any other information which may be associated with acomputing device user. In some embodiments, a fifth data 3027 maycomprise information about a set of computing device users who may sharea same trait (e.g., height, weight, geolocation, age, gender, sex,marital status, configuration, operating system description, etc.) as afirst computing device user.

A fifth data 3027 may comprise a percentage of unique computing deviceusers associated with the at least one trait associated with the firstcomputing device user during a given period. For example, where a firstdata about a first computing device user indicates a trait of “Sex” andwhere a second data about a first computing device user indicates thatthe user is “Female,” a fifth data 3027 may indicate a number,percentage, share, etc. of all computing device users included in anygiven data set that are also “Female.” In some embodiments, a fifth data3027 may indicate a number, percentage, share, etc. of all computingdevice users included in any given data set that are associated with anysecond data value given about a specific trait.

A fifth data 3027 may comprise an indication of the recentness of theinformation (e.g., second data) associated with the at least one traitassociated with the first computing device user. For example, a fifthdata 3027 may indicate whether or not the second data generated orreceived about a first computing device user was obtained within thepast hour, the past day, the past month, the past year, etc. A measureof recentness may comprise any unit of time and is not limited by theexamples given above. A measure (e.g., indication) of recentness may becomparative in nature. For example, in some embodiments, the recentnessof a second data about a first computing device user may be anindication of the relative recentness (e.g., more recent, less recent)compared to a second data associated with another (e.g., second, third,fourth, etc.) computing device user.

An A-code may be generated by transforming (e.g. combining, separating,separating and recombining, reordering, comparing, hashing, encrypting,stacking, organizing, and performing mathematical operations) a fifthdata 3027. In some embodiments, this may include aggregating acollection of fifth data 3027 to generate an A-code 3028 that may beassociated with the comparative activity of the first data 3014.

A method 2000 for generating a communication associated with anoptimization code may comprise storing at least one confirmation code3030 (V-code 3024, C-code 3026, A-code 3028, etc.) at a databaseassociated with the one or more servers. In some embodiments, one ormore (e.g., at least one) confirmation code 3030 (V-code 3024, C-code3026, A-code 3028, a retrieved confirmation code, etc.) may be retrievedfrom a database associated with the one or more servers. In someembodiments, a confirmation code 3030 retrieved from a databaseassociated with the one or more servers may comprise a retrievedconfirmation code.

A method 2000 for generating a communication associated with anoptimization code may comprise generating a raw index 2040. In someembodiments, a raw index 2040 may be generated by transforming (e.g.combining, separating, separating and recombining, reordering,comparing, hashing, encrypting, stacking, organizing, and performingmathematical operations) one or more (e.g., at least one) confirmationcodes 3030. In some embodiments, a raw index 2040 may be generated bytransforming (e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations) one or more (e.g., at least one)confirmation codes 3030 that have been retrieved from a databaseassociated with the one or more servers. In some embodiments, a rawindex 2040 may comprise a list of confirmation codes 3030 associatedwith a user of a computing device (e.g., first computing device, secondcomputing device, third computing device, etc.), which may arranged inany order.

Referring back to FIG. 2, a method 2000 for generating a communicationassociated with an optimization code may comprise generating acomparative index 2050. In some embodiments, a comparative index 2050may be generated by transforming (e.g. combining, separating, separatingand recombining, reordering, comparing, hashing, encrypting, stacking,organizing, and performing mathematical operations) one or more (e.g.,at least one) raw indices 2040 such that the comparative index 2050 maybe based on the one or more raw indices 2040.

A method 2000 for generating a communication associated with anoptimization code may comprise generating a relative locus 2055. In someembodiments, a relative locus 2055 may be generated by transforming(e.g. combining, separating, separating and recombining, reordering,comparing, hashing, encrypting, stacking, organizing, and performingmathematical operations) one or more (e.g., at least one) comparativeindices 2050 such that the relative locus 2055 may be based on the oneor more comparative indices 2050.

A method 2000 for generating a communication associated with anoptimization code may comprise generating an optimization code 2060. Insome embodiments, an optimization code 2060 may be generated bytransforming (e.g. combining, separating, separating and recombining,reordering, comparing, hashing, encrypting, stacking, organizing, andperforming mathematical operations) one or more (e.g., at least one)relative loci 2055 such that the optimization code 2060 may be based onthe one or more relative loci 2055.

The comparative index is then used to mark a relative locus 2055. Therelative locus is then used to generate an optimization code 2060. Theoptimization code, in turn, is used to optimize a communication 2065.

FIG. 4 illustrates an example embodiment wherein one or moreconfirmation codes 4030 are used to generate one or more optimizationcodes 4060. In this embodiment, one or more confirmation codes 4030 maybe transformed to generate a raw index 4040. According to a specificembodiment, the raw index 4040 may be generated by aggregating theweighted averages (e.g., transforming) of each confirmation code 4030.The raw index 4040 may be transformed to generate a comparative index4050. According to a specific embodiment, transforming a raw index 4040may include distributing the values in the raw index 4040 across anormal curve to generate at least one comparative index 4050. Acomparative index 4050 may be transformed to generate a relative locus4055. According to a specific embodiment, transforming a comparativeindex 4050 may include assigning a value that is representative of thenormal curve distribution (e.g., mean, median, mode, inflection point,standard deviation, quartile, etc.) of the comparative index 4050, whichmay comprise a relative locus 4055. In a specific embodiment, a relativelocus 4055 may be representative of the relative predictability (e.g.,reliability, accuracy, dependability, etc.) of the first data. Therelative locus 4055 may be transformed to generate an optimization code4060. The relative locus 4055 may be transformed, according to aspecific embodiment, by standardizing the relative locus 4055. Anoptimization code 4060 may be used to determine parameters about one ormore communications. For example, and without limitation, anoptimization code 4060 may be used to determine whether or not acommunication is sent, the frequency and/or number of communicationsthat get sent, the content of the communications, the recipient of thecommunication, etc.

System Environment

According to some embodiments and as illustrated in FIG. 5, a server5020 may include, among other elements, any combination of a processor5030, a memory 5050, an input/output (I/O) 5070, and a communicationcenter 5080. As described in present embodiments, each of the processor5030, the memory 5050, the I/O 5070, and communication center 5080 mayinclude a plurality of respective units, subunits, and/or elements.Furthermore, each of the processor 5030, the memory 5050, the I/O 5070,and the communication center 5080 may be operatively or otherwisecommunicatively coupled with each other so as to facilitate the methodsand techniques described herein.

The processor 5030 may control any one or more of the memory 5050, theI/O 5070, the communication center 5080, or any other unit which mayinclude the server 5020, as well as any included subunits, elements,components, devices, or functions performed by each or a combination ofthe memory 5050, the I/O 5070, the communication center 5080 or anyother unit which may include the server 5020. Any of the elements orsub-elements of the server 5020 presented here may also be included in asimilar fashion in any of the other units, subunits, and devicesincluded in the system 1000 of FIG. 1. Additionally, any actionsdescribed herein as being performed by a processor 5030 may be taken bythe processor 5030 alone, or by the processor 5030 in conjunction withone or more additional processors, units, subunits, elements,components, devices, and the like. Additionally, while only oneprocessor 5030 may be shown in the figures included here, multipleprocessors may be present or otherwise included in the server 5020, onan external server, or elsewhere in the system 1000 of FIG. 1. Thus,while instructions may be described as being executed by the processor5030 or the various subunits of the processor 5032, 5034, 5036, 5038,the instructions may be executed simultaneously, serially, or otherwiseby one or more multiple processors 5030.

In some embodiments, a processor 5030 may be implemented as one or morecomputer processor (CPU) chips, graphical processor (GPU) chips, or somecombination of CPU chips and GPU chips, and may include a hardwaredevice capable of executing computer instructions. The processor 5030may execute any combination of instructions, codes, computer programs,and scripts. The instructions, codes, computer programs, and scripts maybe received from, stored in, or received from and stored in anycombination of the memory 5050, the I/O 5070, the communication center5080, subunits of the previously described elements, other devices,other computing environments. In some embodiments, non-transitorycomputer-readable medium comprising code may be provided to perform oneor more of the various processes, methods, functions, etc. describedherein.

In some embodiments, the processor 5030 may include, among otherelements, subunits. Subunits may include any combination of a contentmanager 5032, a geolocation finder 5034, a graphical processor 5036, anda resource allocator 5038. Each of these subunits of the processor 5030may be communicatively or otherwise operably coupled with each other.

The content manager 5032 may facilitate any combination of generation,modification, analysis, transmission, and presentation of media contentassociated with methods and systems for network communications. Forexample, the content manager 5032 may control the environment of theapplication during the execution of various processes. For purposes ofillustration and not limitation, media content for which the contentmanager 5032 may be responsible may include any combination ofadvertisements, images, text, themes, audio files, video files,documents, and the like. In some embodiments, the content manager 5032may also interface with any combination of a third-party content server,memory location, and/or a database.

The geolocation finder 5034, particularly in communication withgeolocation information, e.g., provided by GPS subsystems of userdevices, may facilitate any combination of detection, generation,modification, analysis, transmission, and presentation of locationinformation and may provide the geotag embodiment of the third data 3023described in FIG. 3. Location information may include any combination ofglobal positioning system (GPS) coordinates, an internet protocol (IP)address, a media access control (MAC) address, geolocation information,an address, a port number, a zip code, a server number, a proxy name, aproxy number, device information, serial numbers, and the like. In someembodiments, the geolocation finder 5034 may include any one or acombination of various sensors, specifically-purposed hardware elementsfor enabling the geolocation finder 5034 to acquire, measure, andtransform location information.

The graphical processor (GPU) 5036 may facilitate any combination ofgeneration, modification, analysis, processing, transmission, andpresentation of visual content. The GPU 5036 may be configured to rendervisual content for presentation on a user device and/or to analyzevisual content for metadata associated with a user or a user device. Insome embodiments, this visual content may include the display of searchresult and/or activatable communication channels. The GPU 5036 mayinclude multiple GPUs and may therefore be configured to perform and/orexecute multiple processes in parallel.

The resource allocator 5038 may facilitate any one or combination of thedetermination, monitoring, analysis, and allocation of resourcesthroughout the server 5020, the system 1000, any component of the system1000, or other computing environments. For example, the resourceallocator 5038 may facilitate interaction between the server 5020, anysubunit of the server 5020, and a high volume (e.g. multiple) of usersor associated user devices. As such, computing resources of the server5020 utilized by any one or a combination of the processor 5030, thememory 5050, the I/O 5070, the communication center 5080, and anysubunit of these units, such as processing power, data storage space,network bandwidth, and the like may be in high demand at various timesduring operation. Accordingly, the resource allocator 5038 may beconfigured to manage the allocation of various computing resources asthey are required by particular units or particular subunits of theserver 5020.

In some embodiments, the resource allocator 5038 may include sensorsand/or other specially-purposed hardware for monitoring performance ofeach unit and/or subunit of the server 5020, as well as hardware forresponding to the computing resource needs of each unit or subunit. Insome embodiments, the resource allocator 5038 may utilize computingresources of a second computing environment separate and distinct fromthe server 5020 to facilitate a desired operation.

In some embodiments, factors affecting the allocation of computingresources by the resource allocator 5038 may include the number ofongoing user device connections and/or other communication channelconnections, a duration during which computing resources are required byone or more elements of the server 5020, and/or the like. In someembodiments, computing resources may be allocated to and/or distributedamongst a plurality of second computing environments included in theserver 5020 based on one or more factors mentioned above. In someembodiments, the allocation of computing resources of the resourceallocator 5038 may include one or more resource allocators 5038 flippinga switch, adjusting processing power, adjusting memory size,partitioning a memory element, transmitting data, controlling one ormore input and/or output devices, modifying various communicationprotocols, and the like. In some embodiments, the resource allocator5038 may facilitate utilization of parallel processing techniques suchas dedicating a plurality of GPUs included in the processor 5030.

The processor 5030 and any or all of the processor subunits, includingsubunits 5032, 5034, 5036, and 5038, may be used to execute processesinitiated by the methods disclosed in the present application.

In some embodiments, the memory 5050 may be used for one or anycombination of storing, recalling, receiving, transmitting, and/oraccessing various files and/or information during operation of theserver 5020. The memory 5050 may include various types of data storagemedia such as solid state storage media, hard disk storage media, andany other type of data storage medium which may be known to a person ofordinary skill in the art. The memory 5050 may include dedicatedhardware elements such as hard drives and/or servers, as well assoftware elements such as cloud-based storage drives. For example, thememory 5050 may include various subunits such as an operating systemunit 5052, an application data unit 5054, an application programminginterface (API) unit 5056, a content storage unit 5058, a media storageunit 5060, a secure enclave 5062, and/or a cache storage unit 5064.

The memory 5050 and any of its subunits described here may include anyone or any combination of random access memory (RAM), read only memory(ROM), and various forms of secondary storage. RAM may be used to storevolatile data and/or to store instructions that may be executed by theprocessor 5030. For example, the data stored may be any one or acombination of a command, a current operating state of the server 5020,an intended operating state of the server 5020, and the like. As afurther example, data stored in the memory 5050 may include instructionsrelated to various methods and/or functionalities described here. ROMmay be a non-volatile memory device that may have a smaller memorycapacity than the memory capacity of a secondary storage. ROM may beused to store instructions and/or data that may be read during executionof computer instructions. In some embodiments, access to both RAM andROM may be faster than access to secondary storage. Secondary storagemay include one or more disk drives and/or tape drives and may be usedfor non-volatile storage of data or as an over-flow data storage deviceif RAM is not large enough to hold all working data. Secondary storagemay be used to store programs that may be loaded into RAM when suchprograms are selected for execution. In some embodiments, the memory5050 may include one or more databases for storing any data describedhere. Additionally or alternatively, one or more secondary databaseslocated remotely from the server 200 may be utilized and/or accessed bythe memory 5050.

The operating system unit 5052 may facilitate deployment, storage,access, execution, and/or utilization of an operating system utilized bythe server 5020 and/or any other computing environment described herein.In some embodiments, the operating system may include various hardwareand/or software elements that serve as a structural framework forenabling the processor 5030 to execute various operations. The operatingsystem unit 5052 may further store various pieces of information and/ordata associated with operation of the operating system and/or the server5020 as a whole, such as a status of computing resources (e.g.,processing power, memory availability, resource utilization, and/or thelike), runtime information, modules to direct execution of operationsdescribed herein, user permissions, security credentials, and the like.

The application data unit 5054 may facilitate deployment, storage,access, execution, and/or utilization of an application utilized by theserver 5020 or any other computing environment described herein (e.g., auser device). For example, users may be required to download, access,and/or otherwise utilize a software application on a user device such asa smartphone or other internet-enabled device in order for variousoperations described herein to be performed. As such, the applicationdata unit 5054 may store any information and/or data associated with theapplication which may allow the application and/or user device toperform methods associated with network communications. As such,information included in the application data unit 5054 may enable a userto execute various operations described here. The application data unit5054 may further store various pieces of information and/or dataassociated with operation of the application and/or the server 5020 as awhole, such as a status of computing resources (e.g., processing power,memory availability, resource utilization, and/or the like), runtimeinformation, modules to direct execution of operations described herein,user permissions, security credentials, and the like.

The application programming interface (API) unit 5056 may facilitatedeployment, storage, access, execution, and/or utilization ofinformation associated with APIs of the server 5020 and/or any othercomputing environment described herein (e.g., a user device). Forexample, server 5020 may include one or more APIs for enabling variousdevices, applications, and/or computing environments to communicate withthe server 5020, multiple other servers, databases, or other userdevices. Accordingly, the API unit 5056 may include API databasescontaining information that may be accessed and/or utilized byapplications and/or operating systems of other devices and/or computingenvironments associated with network communications. An API may directcommunications between the background component of the user device andthe server 5020. In some embodiments, each API database may beassociated with a customized physical circuit included in the memoryunit 5050 and/or the API unit 5056. Additionally, each API database maybe public and/or private, and so authentication credentials may berequired to access information in an API database.

The content storage unit 5058 may facilitate deployment, storage,access, and/or utilization of information associated with requestedcontent by the server 5020 and/or any other computing environmentdescribed here (e.g., a user device such as a mobile device). Forexample, the content storage unit 5058 may store one or more of images,text, videos, audio content, advertisements, product lists, userrecommendations, and metadata to be presented to a user duringoperations described herein. In some embodiments, the content storageunit 5058 may communicate with the content management unit 5032 toreceive and/or transmit content files.

The media storage unit 5060 may facilitate one or more of deployment,storage, access, analysis, and utilization of media content by theserver 5020 and any other computing environment described herein (e.g.,a user device). Media content may be images, videos, audio files, andany other form of communicative media. For example, the media storageunit 5060 may store communications on system 1000. Further, the mediastorage unit 5060 may store one or more searches, results, imagesassociated with first or second data generated by any unit or subunit ofa server 5020 or user device. Media content generated or used inperforming any of the methods disclosed here may be stored in the mediastorage unit 5060 so that the media content may be analyzed by variouscomponents of the server 5020 both in real time and at a time afterreceipt of the media content. In some embodiments, the media storageunit 5060 may communicate with the GPUs 5036 to facilitate any of theprocesses described here. In some embodiments, media content may includeaudio, images, text, video feeds, and/or any other media contentassociated with methods and systems for network communications.

The secure enclave 5062 may facilitate secure storage of data. In someembodiments, the secure enclave 5062 may include a partitioned portionof storage media included in the memory unit 5050 that is protected byvarious security measures. For example, the secure enclave 5062 may behardware secured. In other embodiments, the secure enclave 5062 mayinclude one or more firewalls, encryption mechanisms, and/or othersecurity-based protocols. Authentication credentials of a user may berequired prior to providing the user access to data stored within thesecure enclave 5062. In some embodiments, the secure enclave 5062 maystore sensitive user information such as sensitive personal data and/ordata associated with the location of a first computing device userthroughout time.

The cache storage unit 5064 may facilitate short-term deployment,storage, access, analysis, and/or utilization of data. In someembodiments, the cache storage unit 5064 may serve as a short-termstorage location for data so that the data stored in the cache storageunit 5064 may be accessed quickly. In some embodiments, the cachestorage unit 5064 may include RAM and/or other storage media types thatenable quick recall of stored data. The cache storage unit 5064 mayinclude a partitioned portion of storage media included in the memory5050.

The data, codes, and indices used to generate the optimization code maybe stored on any or all of the memory subunits, including subunits 5052,5054, 5056, 5058, 5060, 5062, and 5064, of one or more servers.

The I/O unit 5070 may include hardware and/or software elements forenabling the server 5020 to receive, transmit, and/or presentinformation. For example, elements of the I/O unit 5020 may be used toreceive user input from a user via a user device, present results, orcommunications to the user via the user device, present suggestedmatches to the user via a user device, and the like. In this manner, theI/O unit 5070 may enable the server 5020 to interface with a human userin a manner such that the user may use the methods described here. Asdescribed, the I/O unit 5070 may include subunits such as one of, or acombination of, an I/O device 5072, an I/O calibration unit 5074, and/ora media driver 5076.

The I/O device 5070 may facilitate any one or any combination of thereceipt, transmission, processing, presentation, display, input, andoutput of information as a result of executed processes described here.In some embodiments, the I/O device 5070 may include a plurality of I/Odevices. In some embodiments, the U/O device 5070 may include one ormore elements of any one or a combination of a user device, a computingsystem, a server 5020, and a similar device.

The I/O device 5072 may include a variety of elements that enable a userto interface with the server 5020. For example, the I/O device 5072 mayinclude a keyboard, a touchscreen, a button, a sensor, a biometricscanner, a laser, a microphone, a camera, an internet-enabled device,and/or another element for receiving and/or collecting input from auser. Additionally and/or alternatively, the I/O device 5072 may includea display, a screen, a sensor, a vibration mechanism, a light emittingdiode (LED), a speaker, a radio frequency identification (RFID) scanner,and/or another element for presenting and/or otherwise outputting datato a user. In some embodiments, the I/O device 5072 may communicate withone or more elements of the processor 5030 and/or the memory unit 5050to execute operations described herein. For example, the I/O device 5072may include a display, which may utilize the GPU 5036 to present mediacontent stored in the media storage unit 5060 to a user of a userdevice.

The I/O calibration unit 5074 may facilitate the calibration of the I/Odevice 5072. For example, the I/O calibration unit 5074 may detectand/or determine one or more settings of the I/O device 5072, and thenadjust and/or modify settings so that the I/O device 5072 may operatemore efficiently. In some embodiments, the I/O calibration unit 5074 mayutilize a media driver 5076 (or multiple media drivers) to calibrate theI/O device 5072. The media driver 5076 may be installed on a user deviceso that the user device may recognize and/or integrate with the I/Odevice 50724, thereby enabling media content to be displayed, received,generated, and the like. In some embodiments, the I/O device 5072 may becalibrated by the I/O calibration unit 5074 by based on informationincluded in the media driver 5076.

The communication center 5080 may facilitate establishment, maintenance,monitoring, and/or termination of communications between the server 5020and other devices such as user devices, other computing environments,third party server systems, and the like. The communication center 5080may further enable communication between various elements (e.g., unitsand/or subunits) of the server 200 as needed. In some embodiments, thecommunication center 5080 may include a network protocol unit 5082, anAPI gateway 5084, an encryption engine 5086, and/or a communicationdevice 5088. The communication center 5080 may include hardware and/orsoftware elements.

The network protocol unit 5082 may facilitate establishment,maintenance, and/or termination of a communication connection betweenthe server 5020 and another device (e.g. user device) by way of anetwork. For example, the network protocol unit 5082 may detect and/ordefine a communication protocol required by a particular network and/ornetwork type. Communication protocols utilized by the network protocolunit 5082 may include Wi-Fi protocols, Li-Fi protocols, cellular datanetwork protocols. Bluetooth® protocols. WiMAX protocols, Ethernetprotocols, power line communication (PLC) protocols, and the like. Insome embodiments, facilitation of communication between the server 5020and any other device, as well as any element internal to the server5020, may include transforming and/or translating data from beingcompatible with a first communication protocol to being compatible witha second communication protocol. In some embodiments, the networkprotocol unit 5082 may determine and/or monitor an amount of datatraffic to consequently determine which particular network protocol isto be used for establishing a connection with a user device,transmitting data, and/or performing other operations described herein.

The API gateway 5084 may facilitate the enablement of other devicesand/or computing environments to access the API unit 5056 of the memory5050 of the server 5020. For example, a user device may access the APIunit 5056 via the API gateway 5084. In some embodiments, the API gateway5084 may be required to validate user credentials associated with a userof a user device prior to providing access to the API unit 5056 to theuser. The API gateway 5084 may include instructions for enabling theserver 5020 to communicate with another device.

The encryption engine 5086 may facilitate any one or any combination oftranslation, encryption, encoding, decryption, and decoding ofinformation received, transmitted, and/or stored by the server 200. Forexample, the encryption engine 5086 may encrypt data associated with auser's credit card information, etc. Using the encryption engine, eachtransmission of data may be encrypted, encoded, and/or translated forsecurity reasons, and any received data may be encrypted, encoded,and/or translated prior to its processing and/or storage. In someembodiments, the encryption engine 5086 may generate any one orcombination of an encryption key, an encoding key, a translation key,and the like, which may be transmitted along with any data content.

The communication device 5088 may include a variety of hardware and/orsoftware specifically purposed to enable communication between theserver 5020 and another device (e.g. user device), as well ascommunication between elements of the server 5020. In some embodiments,the communication device 5088 may include one or more radiotransceivers, chips, analog front end (AFE) units, antennas, processors,memory, other logic, and/or other components to implement communicationprotocols (wired or wireless) and related functionality for facilitatingcommunication between the server 5020 and any other device. Additionallyand/or alternatively, the communication device 5088 may include a modem,a modem bank, an Ethernet device such as a router or switch, a universalserial bus (USB) interface device, a serial interface, a token ringdevice, a fiber distributed data interface (FDDI) device, a wirelesslocal area network (WLAN) device and/or device component, a radiotransceiver device such as code division multiple access (CDMA) device,a global system for mobile communications (GSM) radio transceiverdevice, a universal mobile telecommunications system (UMTS) radiotransceiver device, a long term evolution (LTE) radio transceiverdevice, a worldwide interoperability for microwave access (WiMAX)device, and/or another device used for communication purposes.

The present disclosure provides several important technical advantagesthat will be readily apparent to one skilled in the art from thefigures, descriptions, and claims. Moreover, while specific advantageshave been enumerated above, various embodiments may include all, some,or none of the enumerated advantages. Any sentence or statement in thisdisclosure may be associated with one or more embodiments. Reference inthe specification to “one embodiment” or “an embodiment” means that aparticular feature, structure, or characteristic described in connectionwith the embodiment is included in at least one embodiment of thedisclosure. The appearances of the phrase “in one embodiment,” or “insome embodiments” in various places in the specification are notnecessarily all referring to the same implementation or embodiment.

Moreover, the above descriptions of the embodiments of the presentdisclosure have been presented for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit the presentdisclosure to the precise form disclosed. Many modifications andvariations are possible in light of the above teaching. As will beunderstood by those familiar with the art, the present disclosure may beembodied in other specific forms without departing from the spirit oressential characteristics thereof. Accordingly, the present disclosureis intended to be illustrative, but not limiting, of the scope of thepresent disclosure.

The invention claimed is:
 1. A method for determining, based on anoptimization code, a parameter for a communication and generating, basedon the parameter, the communication, the method comprising: receiving,at one or more servers and from a first computing device, a first dataassociated with a first computing device user, the first data comprisingat least one trait associated with the first computing device user andwherein the at least one trait is associated with a second data;generating, at the one or more servers, confirmation codes comprising atleast two of: a verification code, wherein the verification code isgenerated based on a comparison of at least one verified traitassociated with the first computing device user to the second dataassociated with the at least one trait associated with the firstcomputing device user, and indicates a comparative accuracy of thesecond data associated with the at least one trait relative to thirddata comprising the at least one verified trait associated with thefirst computing device user; a consistency code, wherein the consistencycode is generated based on a comparison of a fourth data to the firstdata, and indicates a comparative consistency of the first data relativeto the fourth data; and an activity code, wherein the activity code isgenerated based on a comparison of a fifth data to activity datacomprised in the first data and indicates a comparative activity of thefirst data relative to the fifth data; storing the confirmation codes ata database associated with the one or more servers; retrieving, at theone or more servers and from the database associated with the one ormore servers, at least one confirmation code; generating, at the one ormore servers, at least one raw index, wherein the at least one raw indexis based on the at least one confirmation code and wherein the at leastone raw index is generated by transforming the at least one confirmationcode; generating, at the one or more servers, at least one comparativeindex, wherein the at least one comparative index is based on the atleast one raw index and is generated by transforming the at least oneraw index; generating, at the one or more servers, locus data associatedwith the at least one comparative index; generating, at the one or moreservers, the optimization code, wherein the optimization code is basedon the locus data; determining, at the one or more servers, based on theoptimization code, the parameter for the communication; and generating,at the one or more servers, based on the parameter, the communication.2. The method of claim 1, wherein the verification code is generated atthe one or more servers by: receiving the third data from a secondcomputing device, wherein the third data comprises the at least oneverified trait associated with the first computing device user;comparing the at least one verified trait associated with the firstcomputing device user to the second data associated with the at leastone trait associated with the first computing device user; andgenerating, based on the comparing, the verification code.
 3. The methodof claim 1, wherein the consistency code is generated at the one or moreservers by: receiving the fourth data; comparing the fourth data to thefirst data; and generating, based on the comparing, the consistencycode.
 4. The method of claim 1, wherein the activity code is generatedat the one or more servers by: receiving the fifth data; comparing thefifth data to the activity data comprised in the first data: andgenerating, based on the comparing, the activity code.
 5. The method ofclaim 3, wherein the fourth data is associated with one or more of:contamination of the second data associated with the at least one traitassociated with the first computing device user; random user-generateddata, wherein the random user-generated data comprises sixth data notassociated with the at least one trait associated with the firstcomputing device user; and theoretical model data, wherein thetheoretical model data comprises predictions based on historical dataand uses the first data to refine a theoretical model.
 6. The method ofclaim 4, wherein the fifth data is associated with one or more of: thecomparative activity of computing device users associated with the atleast one trait associated with the first computing device user;percentage of unique computing device users associated with the at leastone trait associated with the first computing device user during aperiod; and recentness of information associated with the at least onetrait associated with the first computing device user.
 7. The method ofclaim 1, wherein the confirmation codes comprise the verification code,the consistency code, and the activity code.
 8. The method of claim 1,wherein the second data comprises textual descriptions or categories. 9.The method of claim 1, wherein either the third data comprises thefourth data or the fourth data comprises the third data.
 10. The methodof claim 1, wherein the locus data indicates a dependability,reliability, or accuracy of the first data.
 11. The method of claim 1,wherein the parameter comprises at least one of a frequency, a number, acontent, or a recipient of the communication.
 12. A method fordetermining, based on an optimization code, a parameter for acommunication and generating, based on the parameter, the communication,the method comprising: receiving, at one or more servers and from afirst computing device, a first data associated with a first computingdevice user, the first data comprising at least one trait associatedwith the first computing device user and wherein the at least one traitis associated with a second data; generating at the one or more servers,confirmation codes comprising: a verification code, wherein theverification code is generated at the one or more servers by: receivinga third data from a second computing device, wherein the third datacomprises at least one verified trait associated with the firstcomputing device user, comparing the at least one verified traitassociated with the first computing device user comprised in the thirddata with the second data associated with the at least one traitassociated with the first computing device user, and generating theverification code, wherein the verification code is based on acomparison of the at least one verified trait associated with the firstcomputing device user comprised in the third data with the second dataassociated with the at least one trait associated with the firstcomputing device user and indicates a comparative accuracy of the seconddata associated with the at least one trait relative to the third datacomprising the at least one verified trait associated with the firstcomputing device user; a consistency code, wherein the consistency codeis generated at the one or more servers by: receiving a fourth data,comparing the fourth data to the first data, and generating theconsistency code, wherein the consistency code is based on a comparisonof the fourth data to the first data and indicates a comparativeconsistency of the first data relative to the fourth data; an activitycode, wherein the activity code is generated at the one or more serversby: receiving a fifth data, and generating, based on a comparison ofactivity data comprised in the first data to the fifth data, theactivity code, wherein the activity code indicates a comparativeactivity of the first data relative to the fifth data; storing theconfirmation codes at a database associated with the one or moreservers; retrieving, at the one or more servers and from the databaseassociated with the one or more servers, at least one confirmation code;generating, at the one or more servers, at least one raw index, whereinthe at least one raw index is based on the at least one confirmationcode and wherein the at least one raw index is generated by transformingthe at least one confirmation code; generating, at the one or moreservers, at least one comparative index, wherein the comparative indexis based on the at least one raw index and is generated by transformingthe at least one raw index; generating, at the one or more servers,locus data associated with the at least one comparative index;generating, at the one or more servers, the optimization code, whereinthe optimization code is based on the locus data; determining, at theone or more servers, based on the optimization code, the parameter forthe communication; and generating, at the one or more servers, based onthe parameter, the communication.
 13. The method of claim 12, whereinthe fourth data comprises contaminated data associated with the leastone trait.
 14. A system for determining, based on an optimization code,a parameter for a communication and generating, based on the parameter,the communication, the system comprising a server, the servercomprising: a memory comprising server instructions; and a processingdevice configured for executing the server instructions, wherein theserver instructions cause the processing device to perform operationsof: receiving, from a first computing device, a first data associatedwith a first computing device user, the first data comprising at leastone trait associated with the first computing device user and whereinthe at least one trait is associated with a second data; generatingconfirmation codes comprising at least two of: a verification code,wherein the verification code is generated based on a comparison of atleast one verified trait associated with the first computing device userto the second data associated with the at least one trait associatedwith the first computing device user, and indicates a comparativeaccuracy of the second data associated with the at least one traitrelative to third data comprising the at least one verified traitassociated with the first computing device user; a consistency code,wherein the consistency code is generated based on a comparison of afourth data to the first data; and indicates a comparative consistencyof the first data relative to the fourth data; and an activity code,wherein the activity code is generated based on a comparison of activitydata comprised in the first data to a fifth data, and indicates acomparative activity of the first data relative to the fifth data;storing the confirmation codes at a database associated with the server;retrieving, from the database associated with the server, at least oneretrieved confirmation code; generating at least one raw index, whereinthe at least one raw index is based on the at least one confirmationcode and wherein the at least one raw index is generated by transformingthe at least one confirmation code; generating at least one comparativeindex, wherein the comparative index is based on the at least one rawindex and is generated by transforming the at least one raw index;generating locus data associated with the at least one comparativeindex; generating the optimization code, wherein the optimization codeis based on the locus data; determining, based on the optimization code,the parameter for the communication; and generating, based on theparameter, the communication.
 15. The system of claim 14, wherein theserver instructions cause the processing device to generate theverification code by performing the operations of: receiving the thirddata from a second computing device, wherein the third data comprisesthe at least one verified trait associated with the first computingdevice user; comparing the at least one verified trait associated withthe first computing device user to the second data associated with theat least one trait associated with the first computing device user; andgenerating, based on the comparing, the verification code.
 16. Thesystem of claim 14, wherein the server instructions cause the processingdevice to generate the consistency code by performing the operations of:receiving the fourth data; comparing the fourth data to the first data;and generating, based on the comparing, the consistency code.
 17. Thesystem of claim 14, wherein the server instructions cause the processingdevice to generate the activity code by performing the operations of:receiving the fifth data; comparing the fifth data to the activity datacomprised in the first data: and generating, based on the comparing, theactivity code.
 18. The system of claim 16, wherein the fourth data isassociated with one or more of: contamination of the second dataassociated with the at least one trait associated with the firstcomputing device user; random user-generated data, wherein the randomuser-generated data comprises sixth data not associated with the atleast one trait associated with the first computing device user; andtheoretical model data, wherein the theoretical model data comprisespredictions based on historical data and uses the first data to refine atheoretical model.
 19. The system of claim 17, wherein the fifth data isassociated with one or more of: comparative activity of computing deviceusers associated with the at least one trait associated with the firstcomputing device user; percentage of unique computing device usersassociated with the at least one trait associated with the firstcomputing device user during a period; and recentness of informationassociated with the at least one trait associated with the firstcomputing device user.
 20. The system of claim 14, wherein theconfirmation codes comprise the verification code, the consistency code,and the activity code.